Conventional image quality detection mechanisms are either global (e.g., to assess the quality of an entire image or video) or local (e.g., to assess the quality of a portion of the image or video). When an image includes multiple objects, such as a first object (e.g., a chair) that is blurry and a second object (e.g., a person) that is clear, the conventional image quality detection mechanisms are unable to account for differences in image quality of the different objects.